There is a technique called text mining for analyzing the contents of text. For example, there is a node extraction technique by which the appearance frequency of a pair of nodes (content words or keywords) extracted from a plurality of text data by a morphological analyzer is set as degree of association, and a pair of nodes with a degree of association exceeding a predetermined value is extracted as a pair of associated nodes. By the use of the foregoing technique, a node link is generated such that the higher the degrees of association between extracted pairs of nodes become, the shorter the distances between the nodes become, and the generated node link is displayed. This allows a user to understand the feature of the entire text and visually grasp the degree of association between the nodes.
In addition, there is another technique called OLAP (online analytical processing) for subjecting data registered in a table of a DWH (data warehouse) to multi-dimensional analyses. The OLAP is intended to extract from data, a dimension in which the data is classified into a hierarchical structure (an item set on an axis) and numerical data included in the data, and subject the extracted data to multi-dimensional analyses using methodologies such as “slicing,” “dicing,” and “drill-down.” The “slicing” is a process for subjecting analysis results to more detailed analysis on an axis with a new dimension. The “dicing” is a process for analyzing data in a different dimension (aspect). The “drill-down” is a process for subjecting data to more detailed analysis in a more detailed dimension.    Patent Literature 1: Japanese Laid-open Patent Publication No. 2010-205077    Patent Literature 2: Japanese Laid-open Patent Publication No. 2010-49411    Patent Literature 3: Japanese Laid-open Patent Publication No. 2005-202535    Non-Patent Literature 1: “General Information Manual for Interstage Navigator Explorer Server,” [online], [searched on Jun. 15, 2012], the Internet <http:software.fujitsu.com/jp/manual/manualfiles/M060039/B1 WN7811/02Z200/gai02/gai00013.html>    Non-Patent Literature 2: “General Information Manual for Interstage Navigator Server 8.0,” [online], [searched on Jun. 15, 2012], the Internet <http:software.fujitsu.com/jp/manual/manualfiles/M060059/B1 WN7601/03Z200/gaiaa/gai00086.html>
In some cases, a user may extract from a node link displayed through the foregoing technique for displaying a node link, a node group associated with a specific node and associated with a specific analysis target, by his/her experience or instinct. One example of such extraction by a user will be described. FIG. 26 is a diagram illustrating one example of an operation performed by a user. The example of FIG. 26 provides a node link 90 produced from responses to a plurality of questionnaires from persons who purchased electronic devices such as printers or personal computers in any of three districts, that is, Tobu District, Chubu District, and Seibu District. When the node link 90 illustrated in the example of FIG. 26 is displayed, if a user wishes to search for nodes specific to Tobu District with high degrees of association with the node “hot-selling” possibly inspiring consumers' buying motivation, based on the node link 90 obtained from the questionnaire result, the user performs the following operation. Specifically, the user selects a node group related to the node “hot-selling” and specific to Tobu District as an analysis target by his/her experience or instinct.
However, the user selects a node group by his/her experience or instinct, and thus there are cases where the selected node group is not associated with a specific node or an analysis target.
If a huge number of nodes are included in the node link, it takes enormous time for the user to manually select from the huge number of nodes a node group associated with a specific node and an analysis target.